Pulled from PubMed
Chiara Lazzeri 1, Adriano Peris
Purpose of review: The integration of artificial intelligence into allocation, organ retrieval and transplantation processes represents an innovative approach to address these challenges and enhance the efficiency and effectiveness of healthcare delivery systems. The rationale for applying artificial intelligence in organ transplantation in the elderly is two folds: the increasing number of older deceased donors the increasing number of older recipients in the waiting lists.
Recent findings: To date, older donor and/or older recipients have not specifically focused in artificial intelligence investigations. Age has been considered as a continuous variable in most machine learning prediction models.
Summary: Considering elderly donors, it may be speculated that dedicated datasets should be built, due to the epidemiological changes in donor panorama and the increasing number of older recipients in the waiting lists. So far, only some transplant centers have gained experiences in managing elderly donors, so there is the need of generalized standard protocols for data exchange. To assess organ suitability for transplant, elaborating data from ex vivo machine perfusion would be of utmost importance. Regarding elderly recipients, post-transplant complications (in primis cardiovascular ones) should be considered to elaborate machine learning prediction models for patient outcome.